code: def score_match(query_rep, text, length_penalty, dictionary=None):
      """
      Calculate the score match between the query representation the text.
  
      :param query_rep:
          base query representation to match text again.
      :param text:
          string to compare against query_rep for matching tokens
      :param length_penalty:
          scores are divided by the norm taken to this power
      :param dictionary:
          optional dictionary to use to tokenize text
  
      :returns:
          float score of match
      """
      if text == "":
          return 0
      words = [w for w in dictionary.tokenize(text.lower())]
      score = 0
      rw = query_rep["words"]
      used = {}
      for w in words:
          if w in rw and w not in used:
              score += rw[w]
          used[w] = True
      norm = math.sqrt(len(used))
      norm = math.pow(norm * query_rep["norm"], length_penalty)
      if norm > 1:
          score /= norm
      return score
  
imports: from typing import Optional
  from parlai.core.params import ParlaiParser
  from parlai.core.opt import Opt
  import math
  from collections.abc import Sequence
  import heapq
  import json
  import parlai.utils.torch
  from parlai.core.agents import Agent
  from parlai.core.dict import DictionaryAgent
  from parlai.utils.io import PathManager
label_desc: Use image node_id 1 for calling a global function with example usage: score_match(query_rep, text, length_penalty, dictionary) and returns: score, int